Special Issue on Computational Approaches to Understand and Reduce Energy Consumption in the Built Environment
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The purpose of this special issue is to collect and publish a representative set of manuscripts from the growing community of scholars developing computational approaches to understand and improve energy efficiency in buildings. We are grateful to the editors of the ASCE Journal of Computing of Civil Engineering for supporting this effort and to the academic community for the strong response to our call for papers. It is our hope that by collecting research on this topic, in this special issue the research community can identify synergies between disparate but related research topics, identify and develop new research collaborations, and, ultimately, allow research focused on understanding and reducing energy consumption in the built environment to evolve as a result. Residential and commercial buildings account for about 40% of all energy consumption in the United States. In dense urban settings this figure can increase to up to 80%. Achieving the challenge put forward by the current presidential administration of an 80% reduction in greenhouse gas emissions by 2050 will largely have to come from reductions in energy use by buildings. The International Energy Agency’s (IEA) “Energy Technology Perspectives 2010” report describes that energy efficiency measures can make the largest contribution to reduce energy use over the next 40 years. Civil engineering professionals, being the designers, creators, and stewards of the built environment, will play a key role in the solutions to better understand and reduce energy use. We are excited by the range and diversity of the topics in the special issue, which are listed alphabetically by first author last name, as follows: • “Impact of Social Network Type and Structure on Modeling Normative Energy Use Behavior Interventions” by Kyle Anderson, SangHyun Lee, and Carol Menassa; • “Framework to Evaluate Energy-Saving Potential from Occupancy Interventions in Typical Commercial Buildings in the United States” by Elie Azar and Carol C. Menassa; • “Demonstrating the Impact of the Occupant on Building Performance” by Caroline Clevenger, John Haymaker, and Maral Jalili; • “Automated Diagnostics and Visualization of Potential Energy Performance Problems in Existing Buildings Using Energy Performance Augmented Reality Models” by Mani Golparvar-Fard and Youngjib Ham; • “Network Ecoinformatics: Development of a Social Ecofeedback System to Drive Energy Efficiency in Residential Buildings” by Rimas Gulbinas, Rishee K. Jain, John E. Taylor, Gabriel Peschiera, and Mani Golparvar-Fard; • “Human-Building Interaction Framework for Personalized Thermal Comfort-Driven Systems in Office Buildings” by Farrokh Jazizadeh, Ali Ghahramani, Burcin Becerik-Gerber, Tatiana Kichkaylo, and Michael Orosz; • “Data-Driven Benchmarking of Building Energy Efficiency Utilizing Statistical Frontier Models” by Amir Kavousian and Ram Rajagopal; • “Domain-Specific Querying Formalisms for Retrieving Information about HVAC Systems” by Xuesong Liu, Burcu Akinci, Mario Berges, and James H. Garrett Jr.; and • “Conceptual Framework to Optimize Building Energy Consumption by Coupling Distributed Energy Simulation and Occupancy Models” by Carol C. Menassa, Vineet R. Kamat, SangHyun Lee, Elie Azar, Chen Feng, and Kyle Anderson. In addition, a paper titled “CAD-Centric Attribution Methodology for Multidisciplinary Optimization Environments: Enabling Parametric Attribution for Efficient Design Space Formulation and Evaluation” by Benjamin Welle, John Haymaker, Martin Fischer, and Vladimir Bazjanac will be published in a forthcoming issue. We close this preamble with the hope that this special issue serves as an introduction and becomes one in a series of many future issues focused on special topics in this domain. The opportunity for research on computational approaches to understand and reduce energy consumption in the built environment is vast and research on the topic is nascent. As civil engineers we have a tremendous opportunity for our research to have an impact on an issue of both technological/scientific importance and societal importance. We hope that future special issues can address more specialized subtopics in detail as we work collectively to address energy consumption in the built environment.
[1] Chen Feng,et al. Conceptual Framework to Optimize Building Energy Consumption by Coupling Distributed Energy Simulation and Occupancy Models , 2014, J. Comput. Civ. Eng..
[2] Ram Rajagopal,et al. Data-Driven Benchmarking of Building Energy Efficiency Utilizing Statistical Frontier Models , 2014, J. Comput. Civ. Eng..
[3] Elie Azar,et al. Framework to Evaluate Energy-Saving Potential from Occupancy Interventions in Typical Commercial Buildings in the United States , 2014, J. Comput. Civ. Eng..